Proceedings of the 2024 5th International Conference on Management Science and Engineering Management (ICMSEM 2024)

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Agvs Picking Path Planning Considering Mixed Storage Strategy in Intelligent Warehouse

Authors
Yanju Zhang1, *, Qinggang Yang1
1School of Businessusiness Administrationdministration, Liaoning Technical University, Huludao, Liaoning, 125105, China
*Corresponding author. Email: zhangyanju@lntu.edu.cn
Corresponding Author
Yanju Zhang
Available Online 22 November 2024.
DOI
10.2991/978-94-6463-570-6_119How to use a DOI?
Keywords
intelligent warehouse; mixed storage strategy; conflict-free path planning; improved Q-Learning algorithm
Abstract

To improve the picking efficiency of orders in intelligent warehouses, this article conducts research on the AGV picking path planning problem. Firstly, a mixed storage strategy is introduced based on order characteristics, and a mathematical model is constructed with the objective of minimizing the total time for AGVs to complete all orders. Then, an improved Q-Learning algorithm with a greedy parameter and embedded conflict resolution strategy is proposed to obtain the optimal conflict-free picking path solution. Finally, through numerical comparison and analysis of examples, it is found that compared with existing path planning algorithms, the proposed algorithm reduces the total time for AGVs to complete all orders by 13.79% and 27.82%, respectively. The comparison of indicators such as the number of AGVs used and the proportion of waiting time due to path conflicts verifies that the proposed algorithm and mixed storage strategy can effectively alleviate congestion, reduce the length of driving paths, and improve picking efficiency.

Copyright
© 2024 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the 2024 5th International Conference on Management Science and Engineering Management (ICMSEM 2024)
Series
Advances in Economics, Business and Management Research
Publication Date
22 November 2024
ISBN
978-94-6463-570-6
ISSN
2352-5428
DOI
10.2991/978-94-6463-570-6_119How to use a DOI?
Copyright
© 2024 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Yanju Zhang
AU  - Qinggang Yang
PY  - 2024
DA  - 2024/11/22
TI  - Agvs Picking Path Planning Considering Mixed Storage Strategy in Intelligent Warehouse
BT  - Proceedings of the 2024 5th International Conference on Management Science and Engineering Management (ICMSEM 2024)
PB  - Atlantis Press
SP  - 1190
EP  - 1199
SN  - 2352-5428
UR  - https://doi.org/10.2991/978-94-6463-570-6_119
DO  - 10.2991/978-94-6463-570-6_119
ID  - Zhang2024
ER  -